Different approaches for detecting misinformation by means of novel text analysis tools

 

 

La conferencia también podrá seguirse online en este enlace: https://conectaha.csic.es/b/mic-933-4wr-ose
 

Natural Language Processing (NLP) is still a challenging problem in most research areas. Rumour propagation, clickbait detection, misinformation, fake news, and authorship attribution have become critical in communication systems and social media. Nowadays, with politicians, influencers, and media, the need for truthful information is the most valuable tool. We address the problems of rumor propagation, clickbait detection, and authorship attribution as three different approaches for detecting Fake news and disinformation, and we propose some novel approaches on deep learning architectures and feature construction.

Ponente: Christian Oliva Moya
17 de marzo de 2022, 12:00 horas
C/ Serrano, 144 • Aula III
Entrada libre, aforo limitado

Christian Oliva received the Software and Computer Engineering degree from the Universidad Autónoma de Madrid, Spain, in 2019, and the master’s degree in ICT Research and Innovation in the same university in 2020. Now, he is studying for a Ph.D. degree in Computer Science and Telecommunications. His research interests include machine learning, artificial neural networks, and computational neuroscience.